Methods and systems for handling data received by a state machine engine

ABSTRACT

A data analysis system to analyze data. The data analysis system includes a data buffer configured to receive data to be analyzed. The data analysis system also includes a state machine lattice. The state machine lattice includes multiple data analysis elements and each data analysis element includes multiple memory cells configured to analyze at least a portion of the data and to output a result of the analysis. The data analysis system includes a buffer interface configured to receive the data from the data buffer and to provide the data to the state machine lattice.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a divisional application of U.S. applicationSer. No. 14/992,616, entitled “Methods and Systems for Handling DataReceived by a State Machine Engine,” and filed Jan. 11, 2016, now U.S.Pat. No. 10,366,009 which issued Jul. 30, 2019, which is a divisionalapplication of U.S. application Ser. No. 13/552,479, entitled “Methodsand Systems for Handling Data Received by a State Machine Engine,” andfiled Jul. 18, 2012, now U.S. Pat. No. 9,235,798 which issued on Jan.12, 2016, the entirety of which is incorporated by reference herein forall purposes.

BACKGROUND Field of Invention

Embodiments of the invention relate generally to electronic devices and,more specifically, in certain embodiments, to electronic devices withparallel devices for data analysis.

Description of Related Art

Complex data analysis (e.g., pattern recognition) can be inefficient toperform on a conventional von Neumann based computer. A biologicalbrain, in particular a human brain, however, is adept at performingcomplex data analysis. Current research suggests that a human brainperforms data analysis using a series of hierarchically organized neuronlayers in the neocortex. Neurons in the lower layers of the hierarchyanalyze “raw signals” from, for example, sensory organs, while neuronsin higher layers analyze signal outputs from neurons in the lowerlevels. This hierarchical system in the neocortex, possibly incombination with other areas of the brain, accomplishes the complex dataanalysis that enables humans to perform high level functions such asspatial reasoning, conscious thought, and complex language.

In the field of computing, pattern recognition tasks, for example, areincreasingly challenging. Ever larger volumes of data are transmittedbetween computers, and the number of patterns that users wish to detectis increasing. For example, spam or malware are often detected bysearching for patterns in a data stream, e.g., particular phrases orpieces of code. The number of patterns increases with the variety ofspam and malware, as new patterns may be implemented to search for newvariants. Searching a data stream for each of these patterns can form acomputing bottleneck. Often, as the data stream is received, it issearched for each pattern, one at a time. The delay before the system isready to search the next portion of the data stream increases with thenumber of patterns. Thus, pattern recognition may slow the receipt ofdata.

Hardware has been designed to search a data stream for patterns, butthis hardware often is unable to process adequate amounts of data in anamount of time given. Some devices configured to search a data stream doso by distributing the data stream among a plurality of circuits. Thecircuits each determine whether the data stream matches a portion of apattern. Often, a large number of circuits operate in parallel, eachsearching the data stream at generally the same time. However, there hasnot been a system that effectively allows for performing complex dataanalysis in a manner more comparable to that of a biological brain.Development of such a system is desirable.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 illustrates an example of system having a state machine engine,according to various embodiments of the invention.

FIG. 2 illustrates an example of a finite state machine (FSM) lattice ofthe state machine engine of FIG. 1, according to various embodiments ofthe invention.

FIG. 3 illustrates an example of a block of the FSM lattice of FIG. 2,according to various embodiments of the invention.

FIG. 4 illustrates an example of a row of the block of FIG. 3, accordingto various embodiments of the invention.

FIG. 5 illustrates an example of a Group of Two of the row of FIG. 4,according to various embodiments of the invention.

FIG. 6 illustrates an example of a finite state machine graph, accordingto various embodiments of the invention.

FIG. 7 illustrates an example of two-level hierarchy implemented withFSM lattices, according to various embodiments of the invention.

FIG. 8 illustrates an example of a method for a compiler to convertsource code into a binary file for programming of the FSM lattice ofFIG. 2, according to various embodiments of the invention.

FIG. 9 illustrates a state machine engine, according to variousembodiments of the invention.

FIG. 10 illustrates an example of multiple physical state machineengines arranged in a rank of devices, according to various embodimentsof the invention.

FIG. 11 illustrates an example of data segments grouped into data blocksto be provided to state machine engines, according to variousembodiments of the invention.

FIG. 12 illustrates an example of data padding inserted between the datasegments of the data blocks of FIG. 11, according to various embodimentsof the invention.

FIG. 13 illustrates an example of data padding inserted after datasegments of the data blocks of FIG. 12, according to various embodimentsof the invention

FIG. 14 illustrates an example of the data blocks of FIG. 13 organizedfor transmission to a data buffer system of state machine engines,according to various embodiments of the invention.

FIG. 15 illustrates an example of data blocks received by state machineengines, according to various embodiments of the invention.

FIG. 16 illustrates an example of the data blocks of FIG. 15 stored in adata buffer system of state machine engines, according to variousembodiments of the invention.

FIG. 17 illustrates an example of data being provided from a data buffersystem to multiple FSM lattices, according to various embodiments of theinvention.

FIG. 18 illustrates an example of data being provided into multiplelogical groups, according to various embodiments of the invention.

DETAILED DESCRIPTION

Turning now to the figures, FIG. 1 illustrates an embodiment of aprocessor-based system, generally designated by reference numeral 10.The system 10 (e.g., data analysis system) may be any of a variety oftypes such as a desktop computer, laptop computer, pager, cellularphone, personal organizer, portable audio player, control circuit,camera, etc. The system 10 may also be a network node, such as a router,a server, or a client (e.g., one of the previously-described types ofcomputers). The system 10 may be some other sort of electronic device,such as a copier, a scanner, a printer, a game console, a television, aset-top video distribution or recording system, a cable box, a personaldigital media player, a factory automation system, an automotivecomputer system, or a medical device. (The terms used to describe thesevarious examples of systems, like many of the other terms used herein,may share some referents and, as such, should not be construed narrowlyin virtue of the other items listed.)

In a typical processor-based device, such as the system 10, a processor12, such as a microprocessor, controls the processing of systemfunctions and requests in the system 10. Further, the processor 12 maycomprise a plurality of processors that share system control. Theprocessor 12 may be coupled directly or indirectly to each of theelements in the system 10, such that the processor 12 controls thesystem 10 by executing instructions that may be stored within the system10 or external to the system 10.

In accordance with the embodiments described herein, the system 10includes a state machine engine 14, which may operate under control ofthe processor 12. As used herein, the state machine engine 14 refers toa single device (e.g., single chip). The state machine engine 14 mayemploy any automaton theory. For example, the state machine engine 14may employ one of a number of state machine architectures, including,but not limited to Mealy architectures, Moore architectures, FiniteState Machines (FSMs), Deterministic FSMs (DFSMs), Bit-Parallel StateMachines (BPSMs), etc. Though a variety of architectures may be used,for discussion purposes, the application refers to FSMs. However, thoseskilled in the art will appreciate that the described techniques may beemployed using any one of a variety of state machine architectures.

As discussed further below, the state machine engine 14 may include anumber of (e.g., one or more) finite state machine (FSM) lattices (e.g.,core of a chip). For purposes of this application the term “lattice”refers to an organized framework (e.g., routing matrix, routing network,frame) of elements (e.g., Boolean cells, counter cells, state machineelements, state transition elements). Furthermore, the “lattice” mayhave any suitable shape, structure, or hierarchical organization (e.g.,grid, cube, spherical, cascading). Each FSM lattice may implementmultiple FSMs that each receive and analyze the same data in parallel.Further, the FSM lattices may be arranged in groups (e.g., clusters),such that clusters of FSM lattices may analyze the same input data inparallel. Further, clusters of FSM lattices of the state machine engine14 may be arranged in a hierarchical structure wherein outputs fromstate machine lattices on a lower level of the hierarchical structuremay be used as inputs to state machine lattices on a higher level. Bycascading clusters of parallel FSM lattices of the state machine engine14 in series through the hierarchical structure, increasingly complexpatterns may be analyzed (e.g., evaluated, searched, etc.).

Further, based on the hierarchical parallel configuration of the statemachine engine 14, the state machine engine 14 can be employed forcomplex data analysis (e.g., pattern recognition) in systems thatutilize high processing speeds. For instance, embodiments describedherein may be incorporated in systems with processing speeds of 1GByte/sec. Accordingly, utilizing the state machine engine 14, data fromhigh speed memory devices or other external devices may be rapidlyanalyzed. The state machine engine 14 may analyze a data streamaccording to several criteria (e.g., search terms), at about the sametime, e.g., during a single device cycle. Each of the FSM latticeswithin a cluster of FSMs on a level of the state machine engine 14 mayeach receive the same search term from the data stream at about the sametime, and each of the parallel FSM lattices may determine whether theterm advances the state machine engine 14 to the next state in theprocessing criterion. The state machine engine 14 may analyze termsaccording to a relatively large number of criteria, e.g., more than 100,more than 110, or more than 10,000. Because they operate in parallel,they may apply the criteria to a data stream having a relatively highbandwidth, e.g., a data stream of greater than or generally equal to 1GByte/sec, without slowing the data stream.

In one embodiment, the state machine engine 14 may be configured torecognize (e.g., detect) a great number of patterns in a data stream.For instance, the state machine engine 14 may be utilized to detect apattern in one or more of a variety of types of data streams that a useror other entity might wish to analyze. For example, the state machineengine 14 may be configured to analyze a stream of data received over anetwork, such as packets received over the Internet or voice or datareceived over a cellular network. In one example, the state machineengine 14 may be configured to analyze a data stream for spam ormalware. The data stream may be received as a serial data stream, inwhich the data is received in an order that has meaning, such as in atemporally, lexically, or semantically significant order. Alternatively,the data stream may be received in parallel or out of order and, then,converted into a serial data stream, e.g., by reordering packetsreceived over the Internet. In some embodiments, the data stream maypresent terms serially, but the bits expressing each of the terms may bereceived in parallel. The data stream may be received from a sourceexternal to the system 10, or may be formed by interrogating a memorydevice, such as the memory 16, and forming the data stream from datastored in the memory 16. In other examples, the state machine engine 14may be configured to recognize a sequence of characters that spell acertain word, a sequence of genetic base pairs that specify a gene, asequence of bits in a picture or video file that form a portion of animage, a sequence of bits in an executable file that form a part of aprogram, or a sequence of bits in an audio file that form a part of asong or a spoken phrase. The stream of data to be analyzed may includemultiple bits of data in a binary format or other formats, e.g., baseten, ASCII, etc. The stream may encode the data with a single digit ormultiple digits, e.g., several binary digits.

As will be appreciated, the system 10 may include memory 16. The memory16 may include volatile memory, such as Dynamic Random Access Memory(DRAM), Static Random Access Memory (SRAM), Synchronous DRAM (SDRAM),Double Data Rate DRAM (DDR SDRAM), DDR2 SDRAM, DDR3 SDRAM, etc. Thememory 16 may also include non-volatile memory, such as read-only memory(ROM), PC-RAM, silicon-oxide-nitride-oxide-silicon (SONOS) memory,metal-oxide-nitride-oxide-silicon (MONOS) memory, polysilicon floatinggate based memory, and/or other types of flash memory of variousarchitectures (e.g., NAND memory, NOR memory, etc.) to be used inconjunction with the volatile memory. The memory 16 may include one ormore memory devices, such as DRAM devices, that may provide data to beanalyzed by the state machine engine 14. As used herein, the term“provide” may generically refer to direct, input, insert, send,transfer, transmit, generate, give, output, place, write, etc. Suchdevices may be referred to as or include solid state drives (SSD's),MultimediaMediaCards (MMC's), SecureDigital (SD) cards, CompactFlash(CF) cards, or any other suitable device. Further, it should beappreciated that such devices may couple to the system 10 via anysuitable interface, such as Universal Serial Bus (USB), PeripheralComponent Interconnect (PCI), PCI Express (PCI-E), Small Computer SystemInterface (SCSI), IEEE 1394 (Firewire), or any other suitable interface.To facilitate operation of the memory 16, such as the flash memorydevices, the system 10 may include a memory controller (notillustrated). As will be appreciated, the memory controller may be anindependent device or it may be integral with the processor 12.Additionally, the system 10 may include an external storage 18, such asa magnetic storage device. The external storage may also provide inputdata to the state machine engine 14.

The system 10 may include a number of additional elements. For instance,a compiler 20 may be used to configure (e.g., program) the state machineengine 14, as described in more detail with regard to FIG. 8. An inputdevice 22 may also be coupled to the processor 12 to allow a user toinput data into the system 10. For instance, an input device 22 may beused to input data into the memory 16 for later analysis by the statemachine engine 14. The input device 22 may include buttons, switchingelements, a keyboard, a light pen, a stylus, a mouse, and/or a voicerecognition system, for instance. An output device 24, such as a displaymay also be coupled to the processor 12. The display 24 may include anLCD, a CRT, LEDs, and/or an audio display, for example. They system mayalso include a network interface device 26, such as a Network InterfaceCard (NIC), for interfacing with a network, such as the Internet. Aswill be appreciated, the system 10 may include many other components,depending on the application of the system 10.

FIGS. 2-5 illustrate an example of a FSM lattice 30. In an example, theFSM lattice 30 comprises an array of blocks 32. As will be described,each block 32 may include a plurality of selectively couple-ablehardware elements (e.g., configurable elements and/or special purposeelements) that correspond to a plurality of states in a FSM. Similar toa state in a FSM, a hardware element can analyze an input stream andactivate a downstream hardware element, based on the input stream.

The configurable elements can be configured (e.g., programmed) toimplement many different functions. For instance, the configurableelements may include state machine elements (SMEs) 34, 36 (shown in FIG.5) that are hierarchically organized into rows 38 (shown in FIGS. 3 and4) and blocks 32 (shown in FIGS. 2 and 3). The SMEs may also beconsidered state transition elements (STEs). To route signals betweenthe hierarchically organized SMEs 34, 36, a hierarchy of configurableswitching elements can be used, including inter-block switching elements40 (shown in FIGS. 2 and 3), intra-block switching elements 42 (shown inFIGS. 3 and 4) and intra-row switching elements 44 (shown in FIG. 4).

As described below, the switching elements may include routingstructures and buffers. A SME 34, 36 can correspond to a state of a FSMimplemented by the FSM lattice 30. The SMEs 34, 36 can be coupledtogether by using the configurable switching elements as describedbelow. Accordingly, a FSM can be implemented on the FSM lattice 30 byconfiguring the SMEs 34, 36 to correspond to the functions of states andby selectively coupling together the SMEs 34, 36 to correspond to thetransitions between states in the FSM.

FIG. 2 illustrates an overall view of an example of a FSM lattice 30.The FSM lattice 30 includes a plurality of blocks 32 that can beselectively coupled together with configurable inter-block switchingelements 40. The inter-block switching elements 40 may includeconductors 46 (e.g., wires, traces, etc.) and buffers 48 and 50. In anexample, buffers 48 and 50 are included to control the connection andtiming of signals to/from the inter-block switching elements 40. Asdescribed further below, the buffers 48 may be provided to buffer databeing sent between blocks 32, while the buffers 50 may be provided tobuffer data being sent between inter-block switching elements 40.Additionally, the blocks 32 can be selectively coupled to an input block52 (e.g., a data input port) for receiving signals (e.g., data) andproviding the data to the blocks 32. The blocks 32 can also beselectively coupled to an output block 54 (e.g., an output port) forproviding signals from the blocks 32 to an external device (e.g.,another FSM lattice 30). The FSM lattice 30 can also include aprogramming interface 56 to configure (e.g., via an image, program) theFSM lattice 30. The image can configure (e.g., set) the state of theSMEs 34, 36. That is, the image can configure the SMEs 34, 36 to reactin a certain way to a given input at the input block 52. For example, aSME 34, 36 can be set to output a high signal when the character ‘a’ isreceived at the input block 52.

In an example, the input block 52, the output block 54, and/or theprogramming interface 56 can be implemented as registers such thatwriting to or reading from the registers provides data to or from therespective elements. Accordingly, bits from the image stored in theregisters corresponding to the programming interface 56 can be loaded onthe SMEs 34, 36. Although FIG. 2 illustrates a certain number ofconductors (e.g., wire, trace) between a block 32, input block 52,output block 54, and an inter-block switching element 40, it should beunderstood that in other examples, fewer or more conductors may be used.

FIG. 3 illustrates an example of a block 32. A block 32 can include aplurality of rows 38 that can be selectively coupled together withconfigurable intra-block switching elements 42. Additionally, a row 38can be selectively coupled to another row 38 within another block 32with the inter-block switching elements 40. A row 38 includes aplurality of SMEs 34, 36 organized into pairs of elements that arereferred to herein as groups of two (GOTs) 60. In an example, a block 32comprises sixteen (16) rows 38.

FIG. 4 illustrates an example of a row 38. A GOT 60 can be selectivelycoupled to other GOTs 60 and any other elements (e.g., a special purposeelement 58) within the row 38 by configurable intra-row switchingelements 44. A GOT 60 can also be coupled to other GOTs 60 in other rows38 with the intra-block switching element 42, or other GOTs 60 in otherblocks 32 with an inter-block switching element 40. In an example, a GOT60 has a first and second input 62, 64, and an output 66. The firstinput 62 is coupled to a first SME 34 of the GOT 60 and the second input64 is coupled to a second SME 36 of the GOT 60, as will be furtherillustrated with reference to FIG. 5.

In an example, the row 38 includes a first and second plurality of rowinterconnection conductors 68, 70. In an example, an input 62, 64 of aGOT 60 can be coupled to one or more row interconnection conductors 68,70, and an output 66 can be coupled to one or more row interconnectionconductor 68, 70. In an example, a first plurality of the rowinterconnection conductors 68 can be coupled to each SME 34, 36 of eachGOT 60 within the row 38. A second plurality of the row interconnectionconductors 70 can be coupled to only one SME 34, 36 of each GOT 60within the row 38, but cannot be coupled to the other SME 34, 36 of theGOT 60. In an example, a first half of the second plurality of rowinterconnection conductors 70 can couple to first half of the SMEs 34,36 within a row 38 (one SME 34 from each GOT 60) and a second half ofthe second plurality of row interconnection conductors 70 can couple toa second half of the SMEs 34, 36 within a row 38 (the other SME 34, 36from each GOT 60), as will be better illustrated with respect to FIG. 5.The limited connectivity between the second plurality of rowinterconnection conductors 70 and the SMEs 34, 36 is referred to hereinas “parity”. In an example, the row 38 can also include a specialpurpose element 58 such as a counter, a configurable Boolean logicelement, look-up table, RAM, a field configurable gate array (FPGA), anapplication specific integrated circuit (ASIC), a configurable processor(e.g., a microprocessor), or other element for performing a specialpurpose function.

In an example, the special purpose element 58 comprises a counter (alsoreferred to herein as counter 58). In an example, the counter 58comprises a 12-bit configurable down counter. The 12-bit configurablecounter 58 has a counting input, a reset input, and zero-count output.The counting input, when asserted, decrements the value of the counter58 by one. The reset input, when asserted, causes the counter 58 to loadan initial value from an associated register. For the 12-bit counter 58,up to a 12-bit number can be loaded in as the initial value. When thevalue of the counter 58 is decremented to zero (0), the zero-countoutput is asserted. The counter 58 also has at least two modes, pulseand hold. When the counter 58 is set to pulse mode, the zero-countoutput is asserted when the counter 58 reaches zero and the clockcycles. The zero-count output is asserted during the next clock cycle ofthe counter 58. Resulting in the counter 58 being offset in time fromthe clock cycle. At the next clock cycle, the zero-count output is nolonger asserted. When the counter 58 is set to hold mode the zero-countoutput is asserted during the clock cycle when the counter 58 decrementsto zero, and stays asserted until the counter 58 is reset by the resetinput being asserted.

In another example, the special purpose element 58 comprises Booleanlogic. For example, the Boolean logic may be used to perform logicalfunctions, such as AND, OR, NAND, NOR, Sum of Products (SoP),Negated-Output Sum of Products (NSoP), Negated-Output Product of Sume(NPoS), and Product of Sums (PoS) functions. This Boolean logic can beused to extract data from terminal state SMEs (corresponding to terminalnodes of a FSM, as discussed later herein) in FSM lattice 30. The dataextracted can be used to provide state data to other FSM lattices 30and/or to provide configuring data used to reconfigure FSM lattice 30,or to reconfigure another FSM lattice 30.

FIG. 5 illustrates an example of a GOT 60. The GOT 60 includes a firstSME 34 and a second SME 36 having inputs 62, 64 and having their outputs72, 74 coupled to an OR gate 76 and a 3-to-1 multiplexer 78. The 3-to-1multiplexer 78 can be set to couple the output 66 of the GOT 60 toeither the first SME 34, the second SME 36, or the OR gate 76. The ORgate 76 can be used to couple together both outputs 72, 74 to form thecommon output 66 of the GOT 60. In an example, the first and second SME34, 36 exhibit parity, as discussed above, where the input 62 of thefirst SME 34 can be coupled to some of the row interconnect conductors68 and the input 64 of the second SME 36 can be coupled to other rowinterconnect conductors 70 the common output 66 may be produced whichmay overcome parity problems. In an example, the two SMEs 34, 36 withina GOT 60 can be cascaded and/or looped back to themselves by settingeither or both of switching elements 79. The SMEs 34, 36 can be cascadedby coupling the output 72, 74 of the SMEs 34, 36 to the input 62, 64 ofthe other SME 34, 36. The SMEs 34, 36 can be looped back to themselvesby coupling the output 72, 74 to their own input 62, 64. Accordingly,the output 72 of the first SME 34 can be coupled to neither, one, orboth of the input 62 of the first SME 34 and the input 64 of the secondSME 36.

In an example, a state machine element 34, 36 comprises a plurality ofmemory cells 80, such as those often used in dynamic random accessmemory (DRAM), coupled in parallel to a detect line 82. One such memorycell 80 comprises a memory cell that can be set to a data state, such asone that corresponds to either a high or a low value (e.g., a 1 or 0).The output of the memory cell 80 is coupled to the detect line 82 andthe input to the memory cell 80 receives signals based on data on thedata stream line 84. In an example, an input at the input block 52 isdecoded to select one or more of the memory cells 80. The selectedmemory cell 80 provides its stored data state as an output onto thedetect line 82. For example, the data received at the input block 52 canbe provided to a decoder (not shown) and the decoder can select one ormore of the data stream lines 84. In an example, the decoder can convertan 8-bit ACSII character to the corresponding 1 of 256 data stream lines84.

A memory cell 80, therefore, outputs a high signal to the detect line 82when the memory cell 80 is set to a high value and the data on the datastream line 84 selects the memory cell 80. When the data on the datastream line 84 selects the memory cell 80 and the memory cell 80 is setto a low value, the memory cell 80 outputs a low signal to the detectline 82. The outputs from the memory cells 80 on the detect line 82 aresensed by a detection cell 86.

In an example, the signal on an input line 62, 64 sets the respectivedetection cell 86 to either an active or inactive state. When set to theinactive state, the detection cell 86 outputs a low signal on therespective output 72, 74 regardless of the signal on the respectivedetect line 82. When set to an active state, the detection cell 86outputs a high signal on the respective output line 72, 74 when a highsignal is detected from one of the memory cells 82 of the respective SME34, 36. When in the active state, the detection cell 86 outputs a lowsignal on the respective output line 72, 74 when the signals from all ofthe memory cells 82 of the respective SME 34, 36 are low.

In an example, an SME 34, 36 includes 256 memory cells 80 and eachmemory cell 80 is coupled to a different data stream line 84. Thus, anSME 34, 36 can be programmed to output a high signal when a selected oneor more of the data stream lines 84 have a high signal thereon. Forexample, the SME 34 can have a first memory cell 80 (e.g., bit 0) sethigh and all other memory cells 80 (e.g., bits 1-255) set low. When therespective detection cell 86 is in the active state, the SME 34 outputsa high signal on the output 72 when the data stream line 84corresponding to bit 0 has a high signal thereon. In other examples, theSME 34 can be set to output a high signal when one of multiple datastream lines 84 have a high signal thereon by setting the appropriatememory cells 80 to a high value.

In an example, a memory cell 80 can be set to a high or low value byreading bits from an associated register. Accordingly, the SMEs 34 canbe configured by storing an image created by the compiler 20 into theregisters and loading the bits in the registers into associated memorycells 80. In an example, the image created by the compiler 20 includes abinary image of high and low (e.g., 1 and 0) bits. The image canconfigure the FSM lattice 30 to implement a FSM by cascading the SMEs34, 36. For example, a first SME 34 can be set to an active state bysetting the detection cell 86 to the active state. The first SME 34 canbe set to output a high signal when the data stream line 84corresponding to bit 0 has a high signal thereon. The second SME 36 canbe initially set to an inactive state, but can be set to, when active,output a high signal when the data stream line 84 corresponding to bit 1has a high signal thereon. The first SME 34 and the second SME 36 can becascaded by setting the output 72 of the first SME 34 to couple to theinput 64 of the second SME 36. Thus, when a high signal is sensed on thedata stream line 84 corresponding to bit 0, the first SME 34 outputs ahigh signal on the output 72 and sets the detection cell 86 of thesecond SME 36 to an active state. When a high signal is sensed on thedata stream line 84 corresponding to bit 1, the second SME 36 outputs ahigh signal on the output 74 to activate another SME 36 or for outputfrom the FSM lattice 30.

In an example, a single FSM lattice 30 is implemented on a singlephysical device, however, in other examples two or more FSM lattices 30can be implemented on a single physical device (e.g., physical chip). Inan example, each FSM lattice 30 can include a distinct data input block52, a distinct output block 54, a distinct programming interface 56, anda distinct set of configurable elements. Moreover, each set ofconfigurable elements can react (e.g., output a high or low signal) todata at their corresponding data input block 52. For example, a firstset of configurable elements corresponding to a first FSM lattice 30 canreact to the data at a first data input block 52 corresponding to thefirst FSM lattice 30. A second set of configurable elementscorresponding to a second FSM lattice 30 can react to a second datainput block 52 corresponding to the second FSM lattice 30. Accordingly,each FSM lattice 30 includes a set of configurable elements, whereindifferent sets of configurable elements can react to different inputdata. Similarly, each FSM lattice 30, and each corresponding set ofconfigurable elements can provide a distinct output. In some examples,an output block 54 from a first FSM lattice 30 can be coupled to aninput block 52 of a second FSM lattice 30, such that input data for thesecond FSM lattice 30 can include the output data from the first FSMlattice 30 in a hierarchical arrangement of a series of FSM lattices 30.

In an example, an image for loading onto the FSM lattice 30 comprises aplurality of bits of data for configuring the configurable elements, theconfigurable switching elements, and the special purpose elements withinthe FSM lattice 30. In an example, the image can be loaded onto the FSMlattice 30 to configure the FSM lattice 30 to provide a desired outputbased on certain inputs. The output block 54 can provide outputs fromthe FSM lattice 30 based on the reaction of the configurable elements todata at the data input block 52. An output from the output block 54 caninclude a single bit indicating a match of a given pattern, a wordcomprising a plurality of bits indicating matches and non-matches to aplurality of patterns, and a state vector corresponding to the state ofall or certain configurable elements at a given moment. As described, anumber of FSM lattices 30 may be included in a state machine engine,such as state machine engine 14, to perform data analysis, such aspattern-recognition (e.g., speech recognition, image recognition, etc.)signal processing, imaging, computer vision, cryptography, and others.

FIG. 6 illustrates an example model of a finite state machine (FSM) thatcan be implemented by the FSM lattice 30. The FSM lattice 30 can beconfigured (e.g., programmed) as a physical implementation of a FSM. AFSM can be represented as a diagram 90, (e.g., directed graph,undirected graph, pseudograph), which contains one or more root nodes92. In addition to the root nodes 92, the FSM can be made up of severalstandard nodes 94 and terminal nodes 96 that are connected to the rootnodes 92 and other standard nodes 94 through one or more edges 98. Anode 92, 94, 96 corresponds to a state in the FSM. The edges 98correspond to the transitions between the states.

Each of the nodes 92, 94, 96 can be in either an active or an inactivestate. When in the inactive state, a node 92, 94, 96 does not react(e.g., respond) to input data. When in an active state, a node 92, 94,96 can react to input data. An upstream node 92, 94 can react to theinput data by activating a node 94, 96 that is downstream from the nodewhen the input data matches criteria specified by an edge 98 between theupstream node 92, 94 and the downstream node 94, 96. For example, afirst node 94 that specifies the character ‘b’ will activate a secondnode 94 connected to the first node 94 by an edge 98 when the first node94 is active and the character ‘b’ is received as input data. As usedherein, “upstream” refers to a relationship between one or more nodes,where a first node that is upstream of one or more other nodes (orupstream of itself in the case of a loop or feedback configuration)refers to the situation in which the first node can activate the one ormore other nodes (or can activate itself in the case of a loop).Similarly, “downstream” refers to a relationship where a first node thatis downstream of one or more other nodes (or downstream of itself in thecase of a loop) can be activated by the one or more other nodes (or canbe activated by itself in the case of a loop). Accordingly, the terms“upstream” and “downstream” are used herein to refer to relationshipsbetween one or more nodes, but these terms do not preclude the use ofloops or other non-linear paths among the nodes.

In the diagram 90, the root node 92 can be initially activated and canactivate downstream nodes 94 when the input data matches an edge 98 fromthe root node 92. Nodes 94 can activate nodes 96 when the input datamatches an edge 98 from the node 94. Nodes 94, 96 throughout the diagram90 can be activated in this manner as the input data is received. Aterminal node 96 corresponds to a match of a sequence of interest in theinput data. Accordingly, activation of a terminal node 96 indicates thata sequence of interest has been received as the input data. In thecontext of the FSM lattice 30 implementing a pattern recognitionfunction, arriving at a terminal node 96 can indicate that a specificpattern of interest has been detected in the input data.

In an example, each root node 92, standard node 94, and terminal node 96can correspond to a configurable element in the FSM lattice 30. Eachedge 98 can correspond to connections between the configurable elements.Thus, a standard node 94 that transitions to (e.g., has an edge 98connecting to) another standard node 94 or a terminal node 96corresponds to a configurable element that transitions to (e.g.,provides an output to) another configurable element. In some examples,the root node 92 does not have a corresponding configurable element.

As will be appreciated, although the node 92 is described as a root nodeand nodes 96 are described as terminal nodes, there may not necessarilybe a particular “start” or root node and there may not necessarily be aparticular “end” or output node. In other words, any node may be astarting point and any node may provide output.

When the FSM lattice 30 is programmed, each of the configurable elementscan also be in either an active or inactive state. A given configurableelement, when inactive, does not react to the input data at acorresponding data input block 52. An active configurable element canreact to the input data at the data input block 52, and can activate adownstream configurable element when the input data matches the settingof the configurable element. When a configurable element corresponds toa terminal node 96, the configurable element can be coupled to theoutput block 54 to provide an indication of a match to an externaldevice.

An image loaded onto the FSM lattice 30 via the programming interface 56can configure the configurable elements and special purpose elements, aswell as the connections between the configurable elements and specialpurpose elements, such that a desired FSM is implemented through thesequential activation of nodes based on reactions to the data at thedata input block 52. In an example, a configurable element remainsactive for a single data cycle (e.g., a single character, a set ofcharacters, a single clock cycle) and then becomes inactive unlessre-activated by an upstream configurable element.

A terminal node 96 can be considered to store a compressed history ofpast events. For example, the one or more patterns of input datarequired to reach a terminal node 96 can be represented by theactivation of that terminal node 96. In an example, the output providedby a terminal node 96 is binary, that is, the output indicates whetherthe pattern of interest has been matched or not. The ratio of terminalnodes 96 to standard nodes 94 in a diagram 90 may be quite small. Inother words, although there may be a high complexity in the FSM, theoutput of the FSM may be small by comparison.

In an example, the output of the FSM lattice 30 can comprise a statevector. The state vector comprises the state (e.g., activated or notactivated) of configurable elements of the FSM lattice 30. In anotherexample, the state vector can include the state of all or a subset ofthe configurable elements whether or not the configurable elementscorresponds to a terminal node 96. In an example, the state vectorincludes the states for the configurable elements corresponding toterminal nodes 96. Thus, the output can include a collection of theindications provided by all terminal nodes 96 of a diagram 90. The statevector can be represented as a word, where the binary indicationprovided by each terminal node 96 comprises one bit of the word. Thisencoding of the terminal nodes 96 can provide an effective indication ofthe detection state (e.g., whether and what sequences of interest havebeen detected) for the FSM lattice 30.

As mentioned above, the FSM lattice 30 can be programmed to implement apattern recognition function. For example, the FSM lattice 30 can beconfigured to recognize one or more data sequences (e.g., signatures,patterns) in the input data. When a data sequence of interest isrecognized by the FSM lattice 30, an indication of that recognition canbe provided at the output block 54. In an example, the patternrecognition can recognize a string of symbols (e.g., ASCII characters)to, for example, identify malware or other data in network data.

FIG. 7 illustrates an example of hierarchical structure 100, wherein twolevels of FSM lattices 30 are coupled in series and used to analyzedata. Specifically, in the illustrated embodiment, the hierarchicalstructure 100 includes a first FSM lattice 30A and a second FSM lattice30B arranged in series. Each FSM lattice 30 includes a respective datainput block 52 to receive data input, a programming interface block 56to receive configuring signals and an output block 54.

The first FSM lattice 30A is configured to receive input data, forexample, raw data at a data input block. The first FSM lattice 30Areacts to the input data as described above and provides an output at anoutput block. The output from the first FSM lattice 30A is sent to adata input block of the second FSM lattice 30B. The second FSM lattice30B can then react based on the output provided by the first FSM lattice30A and provide a corresponding output signal 102 of the hierarchicalstructure 100. This hierarchical coupling of two FSM lattices 30A and30B in series provides a means to provide data regarding past events ina compressed word from a first FSM lattice 30A to a second FSM lattice30B. The data provided can effectively be a summary of complex events(e.g., sequences of interest) that were recorded by the first FSMlattice 30A.

The two-level hierarchy 100 of FSM lattices 30A, 30B shown in FIG. 7allows two independent programs to operate based on the same datastream. The two-stage hierarchy can be similar to visual recognition ina biological brain which is modeled as different regions. Under thismodel, the regions are effectively different pattern recognitionengines, each performing a similar computational function (patternmatching) but using different programs (signatures). By connectingmultiple FSM lattices 30A, 30B together, increased knowledge about thedata stream input may be obtained.

The first level of the hierarchy (implemented by the first FSM lattice30A) can, for example, perform processing directly on a raw data stream.That is, a raw data stream can be received at an input block 52 of thefirst FSM lattice 30A and the configurable elements of the first FSMlattice 30A can react to the raw data stream. The second level(implemented by the second FSM lattice 30B) of the hierarchy can processthe output from the first level. That is, the second FSM lattice 30Breceives the output from an output block 54 of the first FSM lattice 30Aat an input block 52 of the second FSM lattice 30B and the configurableelements of the second FSM lattice 30B can react to the output of thefirst FSM lattice 30A. Accordingly, in this example, the second FSMlattice 30B does not receive the raw data stream as an input, but ratherreceives the indications of patterns of interest that are matched by theraw data stream as determined by the first FSM lattice 30A. The secondFSM lattice 30B can implement a FSM that recognizes patterns in theoutput data stream from the first FSM lattice 30A. It should beappreciated that the second FSM lattice 30B may receive inputs frommultiple other FSM lattices in addition to receiving output from the FSMlattice 30A. Likewise, the second FSM lattice 30B may receive inputsfrom other devices. The second FSM lattice 30B may combine thesemultiple inputs to produce outputs.

FIG. 8 illustrates an example of a method 110 for a compiler to convertsource code into an image used to configure a FSM lattice, such aslattice 30, to implement a FSM. Method 110 includes parsing the sourcecode into a syntax tree (block 112), converting the syntax tree into anautomaton (block 114), optimizing the automaton (block 116), convertingthe automaton into a netlist (block 118), placing the netlist onhardware (block 120), routing the netlist (block 122), and publishingthe resulting image (block 124).

In an example, the compiler 20 includes an application programminginterface (API) that allows software developers to create images forimplementing FSMs on the FSM lattice 30. The compiler 20 providesmethods to convert an input set of regular expressions in the sourcecode into an image that is configured to configure the FSM lattice 30.The compiler 20 can be implemented by instructions for a computer havinga von Neumann architecture. These instructions can cause a processor 12on the computer to implement the functions of the compiler 20. Forexample, the instructions, when executed by the processor 12, can causethe processor 12 to perform actions as described in blocks 112, 114,116, 118, 120, 122, and 124 on source code that is accessible to theprocessor 12.

In an example, the source code describes search strings for identifyingpatterns of symbols within a group of symbols. To describe the searchstrings, the source code can include a plurality of regular expressions(regexs). A regex can be a string for describing a symbol searchpattern. Regexes are widely used in various computer domains, such asprogramming languages, text editors, network security, and others. In anexample, the regular expressions supported by the compiler includecriteria for the analysis of unstructured data. Unstructured data caninclude data that is free form and has no indexing applied to wordswithin the data. Words can include any combination of bytes, printableand non-printable, within the data. In an example, the compiler cansupport multiple different source code languages for implementingregexes including Perl, (e.g., Perl compatible regular expressions(PCRE)), PHP, Java, and .NET languages.

At block 112 the compiler 20 can parse the source code to form anarrangement of relationally connected operators, where different typesof operators correspond to different functions implemented by the sourcecode (e.g., different functions implemented by regexes in the sourcecode). Parsing source code can create a generic representation of thesource code. In an example, the generic representation comprises anencoded representation of the regexs in the source code in the form of atree graph known as a syntax tree. The examples described herein referto the arrangement as a syntax tree (also known as an “abstract syntaxtree”) in other examples, however, a concrete syntax tree or otherarrangement can be used.

Since, as mentioned above, the compiler 20 can support multiplelanguages of source code, parsing converts the source code, regardlessof the language, into a non-language specific representation, e.g., asyntax tree. Thus, further processing (blocks 114, 116, 118, 120) by thecompiler 20 can work from a common input structure regardless of thelanguage of the source code.

As noted above, the syntax tree includes a plurality of operators thatare relationally connected. A syntax tree can include multiple differenttypes of operators. That is, different operators can correspond todifferent functions implemented by the regexes in the source code.

At block 114, the syntax tree is converted into an automaton. Anautomaton comprises a software model of a FSM and can accordingly beclassified as deterministic or non-deterministic. A deterministicautomaton has a single path of execution at a given time, while anon-deterministic automaton has multiple concurrent paths of execution.The automaton comprises a plurality of states. In order to convert thesyntax tree into an automaton, the operators and relationships betweenthe operators in the syntax tree are converted into states withtransitions between the states. In an example, the automaton can beconverted based partly on the hardware of the FSM lattice 30.

In an example, input symbols for the automaton include the symbols ofthe alphabet, the numerals 0-9, and other printable characters. In anexample, the input symbols are represented by the byte values 0 through255 inclusive. In an example, an automaton can be represented as adirected graph where the nodes of the graph correspond to the set ofstates. In an example, a transition from state p to state q on an inputsymbol α, i.e. δ(p, α), is shown by a directed connection from node p tonode q. In an example, a reversal of an automaton produces a newautomaton where each transition p→q on some symbol a is reversed q→p onthe same symbol. In a reversal, start state becomes a final state andthe final states become start states. In an example, the languagerecognized (e.g., matched) by an automaton is the set of all possiblecharacter strings which when input sequentially into the automaton willreach a final state. Each string in the language recognized by theautomaton traces a path from the start state to one or more finalstates.

At block 116, after the automaton is constructed, the automaton isoptimized to reduce its complexity and size, among other things. Theautomaton can be optimized by combining redundant states.

At block 118, the optimized automaton is converted into a netlist.Converting the automaton into a netlist maps each state of the automatonto a hardware element (e.g., SMEs 34, 36, other elements) on the FSMlattice 30, and determines the connections between the hardwareelements.

At block 120, the netlist is placed to select a specific hardwareelement of the target device (e.g., SMEs 34, 36, special purposeelements 58) corresponding to each node of the netlist. In an example,placing selects each specific hardware element based on general inputand output constraints for of the FSM lattice 30.

At block 122, the placed netlist is routed to determine the settings forthe configurable switching elements (e.g., inter-block switchingelements 40, intra-block switching elements 42, and intra-row switchingelements 44) in order to couple the selected hardware elements togetherto achieve the connections describe by the netlist. In an example, thesettings for the configurable switching elements are determined bydetermining specific conductors of the FSM lattice 30 that will be usedto connect the selected hardware elements, and the settings for theconfigurable switching elements. Routing can take into account morespecific limitations of the connections between the hardware elementsthat placement at block 120. Accordingly, routing may adjust thelocation of some of the hardware elements as determined by the globalplacement in order to make appropriate connections given the actuallimitations of the conductors on the FSM lattice 30.

Once the netlist is placed and routed, the placed and routed netlist canbe converted into a plurality of bits for configuring a FSM lattice 30.The plurality of bits are referred to herein as an image (e.g., binaryimage).

At block 124, an image is published by the compiler 20. The imagecomprises a plurality of bits for configuring specific hardware elementsof the FSM lattice 30. The bits can be loaded onto the FSM lattice 30 toconfigure the state of SMEs 34, 36, the special purpose elements 58, andthe configurable switching elements such that the programmed FSM lattice30 implements a FSM having the functionality described by the sourcecode. Placement (block 120) and routing (block 122) can map specifichardware elements at specific locations in the FSM lattice 30 tospecific states in the automaton. Accordingly, the bits in the image canconfigure the specific hardware elements to implement the desiredfunction(s). In an example, the image can be published by saving themachine code to a computer readable medium. In another example, theimage can be published by displaying the image on a display device. Instill another example, the image can be published by sending the imageto another device, such as a configuring device for loading the imageonto the FSM lattice 30. In yet another example, the image can bepublished by loading the image onto a FSM lattice (e.g., the FSM lattice30).

In an example, an image can be loaded onto the FSM lattice 30 by eitherdirectly loading the bit values from the image to the SMEs 34, 36 andother hardware elements or by loading the image into one or moreregisters and then writing the bit values from the registers to the SMEs34, 36 and other hardware elements. In an example, the hardware elements(e.g., SMEs 34, 36, special purpose elements 58, configurable switchingelements 40, 42, 44) of the FSM lattice 30 are memory mapped such that aconfiguring device and/or computer can load the image onto the FSMlattice 30 by writing the image to one or more memory addresses.

Method examples described herein can be machine or computer-implementedat least in part. Some examples can include a computer-readable mediumor machine-readable medium encoded with instructions operable toconfigure an electronic device to perform methods as described in theabove examples. An implementation of such methods can include code, suchas microcode, assembly language code, a higher-level language code, orthe like. Such code can include computer readable instructions forperforming various methods. The code may form portions of computerprogram products. Further, the code may be tangibly stored on one ormore volatile or non-volatile computer-readable media during executionor at other times. These computer-readable media may include, but arenot limited to, hard disks, removable magnetic disks, removable opticaldisks (e.g., compact disks and digital video disks), magnetic cassettes,memory cards or sticks, random access memories (RAMs), read onlymemories (ROMs), and the like.

Referring now to FIG. 9, an embodiment of the state machine engine 14(e.g., a single device on a single chip) is illustrated. As previouslydescribed, the state machine engine 14 is configured to receive datafrom a source, such as the memory 16 over a data bus. In the illustratedembodiment, data may be sent to the state machine engine 14 through abus interface, such as a double data rate three (DDR3) bus interface130. The DDR3 bus interface 130 may be capable of exchanging (e.g.,providing and receiving) data at a rate greater than or equal to 1GByte/sec. Such a data exchange rate may be greater than a rate thatdata is analyzed by the state machine engine 14. As will be appreciated,depending on the source of the data to be analyzed, the bus interface130 may be any suitable bus interface for exchanging data to and from adata source to the state machine engine 14, such as a NAND Flashinterface, peripheral component interconnect (PCI) interface, gigabitmedia independent interface (GMMI), etc. As previously described, thestate machine engine 14 includes one or more FSM lattices 30 configuredto analyze data. Each FSM lattice 30 may be divided into twohalf-lattices. In the illustrated embodiment, each half lattice mayinclude 24K SMEs (e.g., SMEs 34, 36), such that the lattice 30 includes48K SMEs. The lattice 30 may comprise any desirable number of SMEs,arranged as previously described with regard to FIGS. 2-5. Further,while only one FSM lattice 30 is illustrated, the state machine engine14 may include multiple FSM lattices 30, as previously described.

Data to be analyzed may be received at the bus interface 130 andprovided to the FSM lattice 30 through a number of buffers and bufferinterfaces. In the illustrated embodiment, the data path includes databuffers 132, an instruction buffer 133, process buffers 134, and aninter-rank (IR) bus and process buffer interface 136. The data buffers132 are configured to receive and temporarily store data to be analyzed.In one embodiment, there are two data buffers 132 (data buffer A anddata buffer B). Data may be stored in one of the two data buffers 132,while data is being emptied from the other data buffer 132, for analysisby the FSM lattice 30. The bus interface 130 may be configured toprovide data to be analyzed to the data buffers 132 until the databuffers 132 are full. After the data buffers 132 are full, the businterface 130 may be configured to be free to be used for other purposes(e.g., to provide other data from a data stream until the data buffers132 are available to receive additional data to be analyzed). In theillustrated embodiment, the data buffers 132 may be 32 KBytes each. Theinstruction buffer 133 is configured to receive instructions from theprocessor 12 via the bus interface 130, such as instructions thatcorrespond to the data to be analyzed and instructions that correspondto configuring the state machine engine 14. The IR bus and processbuffer interface 136 may facilitate providing data to the process buffer134. The IR bus and process buffer interface 136 can be used to ensurethat data is processed by the FSM lattice 30 in order. The IR bus andprocess buffer interface 136 may coordinate the exchange of data, timingdata, packing instructions, etc. such that data is received and analyzedcorrectly. Generally, the IR bus and process buffer interface 136 allowsthe use of multiple devices in a rank of devices. The multiple devicesin the rank of devices share data such that all of the multiple devicesreceive all of the shared data in the correct order. For example,multiple physical devices (e.g., state machine engines 14, chips,separate devices) may be arranged in a rank and may provide data to eachother via the IR bus and process buffer interface 136. For purposes ofthis application the term “rank” refers to a set of state machineengines 14 connected to the same chip select. In the illustratedembodiment, the IR bus and process buffer interface 136 may include an 8bit data bus.

In the illustrated embodiment, the state machine engine 14 also includesa de-compressor 138 and a compressor 140 to aid in providing data to andfrom the state machine engine 14. As may be appreciated, the compressor140 and de-compressor 138 may use the same compression algorithms tosimplify software and/or hardware designs; however, the compressor 140and the de-compressor 138 may also use different algorithms. Bycompressing the data, the bus interface 130 (e.g., DDR3 bus interface)utilization time may be minimized. In the present embodiment, thecompressor 140 may be used to compress state vector data, configurationdata (e.g., programming data), and match results data obtained afteranalysis by the FSM lattice 30. In one embodiment, the compressor 140and de-compressor 138 may be disabled (e.g., turned off) such that dataflowing to and/or from the compressor 140 and de-compressor 138 is notmodified (e.g., neither compressed nor de-compressed).

The compressor 140 and de-compressor 138 can also be configured tohandle multiple sets of data and each set of data may be of varyinglengths. By “padding” compressed data and including an indicator as towhen each compressed region ends, the compressor 140 may improve theoverall processing speed through the state machine engine 14.

The state machine engine 14 includes a state vector system 141 having astate vector cache memory 142, a state vector memory buffer 144, a statevector intermediate input buffer 146, and a state vector intermediateoutput buffer 148. The state vector system 141 may be used to storemultiple state vectors of the FSM lattice 30, to move state vectors ontoor off of the state machine engine 14, and to provide a state vector tothe FSM lattice 30 to restore the FSM lattice 30 to a statecorresponding to the provided state vector. For example, each statevector may be temporarily stored in the state vector cache memory 142.That is, the state of each SME 34, 36 may be stored, such that the statemay be restored and used in further analysis at a later time, whilefreeing the SMEs 34, 36 for analysis of a new data set (e.g., searchterm). Like a typical cache, the state vector cache memory 142 allowsstorage of state vectors for quick retrieval and use, here by the FSMlattice 30, for instance. In the illustrated embodiment, the statevector cache memory 142 may store up to 512 state vectors. Each statevector comprises the state (e.g., activated or not activated) of theSMEs 34, 36 of the FSM lattice 30 and the dynamic (e.g., current) countof the counters 58.

As will be appreciated, the state vector data may be exchanged betweendifferent state machine engines 14 (e.g., chips) in a rank. The statevector data may be exchanged between the different state machine engines14 for various purposes such as: to synchronize the state of the SMEs34, 36 of the FSM lattices 30 and the dynamic count of the counters 58,to perform the same functions across multiple state machine engines 14,to reproduce results across multiple state machine engines 14, tocascade results across multiple state machine engines 14, to store ahistory of states of the SMEs 34, 36 and the dynamic count of thecounters 58 used to analyze data that is cascaded through multiple statemachine engines 14, and so forth. Furthermore, it should be noted thatwithin a state machine engine 14, the state vector data may be used toquickly restore the state vector. For example, the state vector data maybe used to restore the state of the SMEs 34, 36 and the dynamic count ofthe counters 58 to an initialized state (e.g., to search for a newsearch term), to restore the state of the SMEs 34, 36 and the dynamiccount of the counters 58 to prior state (e.g., to search for apreviously searched search term), and to change the state of the SMEs34, 36 and the dynamic count of the counters 58 to be configured for acascading configuration (e.g., to search for a search term in acascading search). In certain embodiments, the state vector data may beprovided to the bus interface 130 so that the state vector data may beprovided to the processor 12 (e.g., for analysis of the state vectordata, reconfiguring the state vector data to apply modifications,reconfiguring the state vector data to improve efficiency, and soforth).

For example, in certain embodiments, the state machine engine 14 mayprovide cached state vector data (e.g., data stored by the state vectorsystem 141) from the FSM lattice 30 to an external device. The externaldevice may receive the state vector data, modify the state vector data,and provide the modified state vector data to the state machine engine14 for restoring the FSM lattice 30 (e.g., resetting, initializing).Accordingly, the external device may modify the state vector data sothat the state machine engine 14 may skip states (e.g., jump around) asdesired.

The state vector cache memory 142 may receive state vector data from anysuitable device. For example, the state vector cache memory 142 mayreceive a state vector from the FSM lattice 30, another FSM lattice 30(e.g., via the IR bus and process buffer interface 136), thede-compressor 138, and so forth. In the illustrated embodiment, thestate vector cache memory 142 may receive state vectors from otherdevices via the state vector memory buffer 144. Furthermore, the statevector cache memory 142 may provide state vector data to any suitabledevice. For example, the state vector cache memory 142 may provide statevector data to the state vector memory buffer 144, the state vectorintermediate input buffer 146, and the state vector intermediate outputbuffer 148.

Additional buffers, such as the state vector memory buffer 144, statevector intermediate input buffer 146, and state vector intermediateoutput buffer 148, may be utilized in conjunction with the state vectorcache memory 142 to accommodate rapid retrieval and storage of statevectors, while processing separate data sets with interleaved packetsthrough the state machine engine 14. In the illustrated embodiment, eachof the state vector memory buffer 144, the state vector intermediateinput buffer 146, and the state vector intermediate output buffer 148may be configured to temporarily store one state vector. The statevector memory buffer 144 may be used to receive state vector data fromany suitable device and to provide state vector data to any suitabledevice. For example, the state vector memory buffer 144 may be used toreceive a state vector from the FSM lattice 30, another FSM lattice 30(e.g., via the IR bus and process buffer interface 136), thede-compressor 138, and the state vector cache memory 142. As anotherexample, the state vector memory buffer 144 may be used to provide statevector data to the IR bus and process buffer interface 136 (e.g., forother FSM lattices 30), the compressor 140, and the state vector cachememory 142.

Likewise, the state vector intermediate input buffer 146 may be used toreceive state vector data from any suitable device and to provide statevector data to any suitable device. For example, the state vectorintermediate input buffer 146 may be used to receive a state vector froman FSM lattice 30 (e.g., via the IR bus and process buffer interface136), the de-compressor 138, and the state vector cache memory 142. Asanother example, the state vector intermediate input buffer 146 may beused to provide a state vector to the FSM lattice 30. Furthermore, thestate vector intermediate output buffer 148 may be used to receive astate vector from any suitable device and to provide a state vector toany suitable device. For example, the state vector intermediate outputbuffer 148 may be used to receive a state vector from the FSM lattice 30and the state vector cache memory 142. As another example, the statevector intermediate output buffer 148 may be used to provide a statevector to an FSM lattice 30 (e.g., via the IR bus and process bufferinterface 136) and the compressor 140.

Once a result of interest is produced by the FSM lattice 30, matchresults may be stored in a match results memory 150. That is, a “matchvector” indicating a match (e.g., detection of a pattern of interest)may be stored in the match results memory 150. The match result can thenbe sent to a match buffer 152 for transmission over the bus interface130 to the processor 12, for example. As previously described, the matchresults may be compressed.

Additional registers and buffers may be provided in the state machineengine 14, as well. For instance, the state machine engine 14 mayinclude control and status registers 154. In addition, restore andprogram buffers 156 may be provided for use in configuring the SMEs 34,36 of the FSM lattice 30 initially, or restoring the state of the SMEs34, 36 in the FSM lattice 30 during analysis. Similarly, save and repairmap buffers 158 may also be provided for storage of save and repair mapsfor setup and usage.

FIG. 10 illustrates an example multiple physical state machine engines14 arranged in a rank of devices. As previously described, data to beanalyzed is received at the bus interface 130. The bus interface 130directs the data to a data buffer system 159 which includes the databuffers 132 and the instruction buffer 133 of each state machine engine14 (e.g., F0, F1, F2, F3, F4, F5, F6, F7). The data buffers 132 areconfigured to receive and temporarily store data to be analyzed. In theillustrated embodiment, there are two data buffers 132 (e.g., databuffer A and data buffer B) in each state machine engine 14. Data may bestored in one of the two data buffers 132, while data is being emptiedfrom the other data buffer 132, for analysis by an FSM lattice 30. Aspreviously discussed, the instruction buffer 133 is configured toreceive instructions from the processor 12 via the bus interface 130,such as instructions that correspond to the data to be analyzed. Fromthe data buffer system 159, data to be analyzed and instructions thatcorrespond to the data are provided to one or more of the FSM lattices30 (e.g., Fa, Fb, Fc, Fd, Fe, Ff, Fg, Fh) via the IR bus and processbuffer interface 136. In the present embodiment, the physical FSMlattices 30 are arranged into logical groups. Specifically, Fg and Fhare arranged into a logical group A 162, Fe and Ff are arranged into alogical group B 164, Fc and Fd are arranged into a logical group C 166,and Fa and Fb are arranged into a logical group D 168. Furthermore, aswill be appreciated, data may be exchanged between the FSM lattices 30and another device (e.g., FSM lattice 30) via the IR bus and processbuffer interface 136. For example, the IR bus and process bufferinterface 136 may be used to exchange data between any of the FSMlattices 30. Although eight state machine engines 14 are illustrated,the rank of devices may have any suitable number of state machineengines 14 (e.g., 1, 2, 4, 8, and so forth). As will be appreciated, theIR bus and process buffer interface 136 may include an input forreceiving data (e.g., from the data buffer system 159 and the FSMlattices 30). Likewise, the IR bus and process buffer interface 136 mayinclude an output for sending data (e.g., to the FSM lattices 30).

The bus interface 130 may receive data to be analyzed in a format thatis tailored for efficient use of the data. Specifically, FIGS. 11 to 14illustrate examples of how data may be assigned (e.g., grouped) by theprocessor 12 into data blocks that are provided to the state machineengines 14 via the bus interface 130. Furthermore, FIGS. 15 to 17illustrate examples of how data blocks may be received, stored, andprovided via the data buffer system 159 of the state machine engines 14.FIG. 18 illustrates how data blocks may be received by the logicalgroups 162, 164, 166, and 168.

Referring now to FIG. 11, an example of data segments (e.g., data set,search term) assigned by the processor 12 into data blocks to beprovided to the state machine engines 14 is illustrated. In the presentembodiment, multiple data segments are assigned into a single datablock. Each data block is assigned to be analyzed by a single logicalgroup of FSM lattices 30 (e.g., on one or more state machine engines 14in a rank of state machine engines 14). For example, a data stream 170(e.g., a large amount of data to be sent by the processor 12 to thestate machine engines 14) is assigned by the processor 12 into: a firstdata block 172 that corresponds to data intended for the logical group A162, a second data block 174 that corresponds to data intended for thelogical group B 164, a third data block 176 that corresponds to dataintended for the logical group C 166, and a fourth data block 178 thatcorresponds to data intended for the logical group D 168. Specifically,the data stream 170 is divided by the processor 12 into data segments180, 182, 184, 186, 188, 190, 192, 194, 196, 198, and 200. As will beappreciated, each of the data segments 180, 182, 184, 186, 188, 190,192, 194, 196, 198, and 200 may represent a data set to be analyzed byan FSM lattice 30. As will be appreciated, the processor 12 may assigndata segments 180, 182, 184, 186, 188, 190, 192, 194, 196, 198, and 200to the data blocks 172, 174, 176, and 178 for any suitable reason. Forexample, the processor 12 may assign data segments to certain datablocks based on a length of each data set and/or an order that data setsare to be analyzed in order to process the data sets efficiently.

The data segments 180, 182, 184, 186, 188, 190, 192, 194, 196, 198, and200 may be assigned into the data blocks 172, 174, 176, and 178 usingany suitable manner. For example, the data segments 180, 182, 184, 186,188, 190, 192, 194, 196, 198, and 200 may be assigned into data blocks172, 174, 176, and 178 such that a number of bytes in the data blocks172, 174, 176, and 178 is minimized. As another example, the datasegments 180, 182, 184, 186, 188, 190, 192, 194, 196, 198, and 200 maybe assigned into data blocks 172, 174, 176, and 178 such that certaindata segments are grouped together.

As illustrated, the first data block 172 includes the data segment A180, the data segment F 190, and the data segment I 196. The second datablock 174 includes the data segment B 182 and the data segment K 200.Furthermore, the third data block 176 includes the data segment C 184,the data segment E 188, and the data segment G 192. The fourth datablock 178 includes the data segment D 186, the data segment H 194, andthe data segment J 198.

As will be appreciated, to process the data blocks efficiently, the datablocks may all have an equal amount of data. Furthermore, the datasegments within the data blocks may start and/or stop at predeterminedintervals (e.g., bytes, words) within the data blocks so that processingdevices can determine when data segments start and stop. However, thedata segments may not have the correct amount of data to start and/orstop at the predetermined intervals. Accordingly, data padding may beinserted between certain data segments so that data starts and/or stopswithin the data blocks at the predetermined intervals. In addition, datapadding may be added to the end of a data block so that all data blockshave an equal amount of data.

Referring now to FIG. 12, an example of data padding inserted betweenthe data segments of the data blocks 172, 174, 176, and 178 of FIG. 11is illustrated. For example, in the first data block 172, data padding202 may be inserted between the data segment A 180 and the data segmentF 190. Further, data padding 204 may be inserted between the datasegment F 190 and the data segment I 196. As another example, in thesecond data block 174, data padding 206 may be inserted between the datasegment B182 and the data segment K 200. In the third data block 176,data padding 208 may be inserted between the data segment C 184 and thedata segment E 188. Likewise, data padding 210 may be inserted betweenthe data segment E 188 and the data segment G 192. As another example,in the fourth data block 178, data padding 212 may be inserted betweenthe data segment D 186 and the data segment H 194. In addition, datapadding 214 may be inserted between the data segment H 194 and the datasegment J 198.

The data padding 202, 204, 206, 208, 210, 212, and 214 may include anysuitable number of bytes of data that are not to be analyzed (e.g.,invalid data, junk data, filler data, garbage data, etc.). In oneembodiment, the number of bytes used as data padding may be a number ofbytes that when added to a number of bytes of the prior data segmentreach a whole word boundary (i.e., a number of bytes of the prior datasegment plus the number of bytes used as data padding is equallydivisible by the whole word boundary). For example, a number of bytes ofthe data padding 202 may be such that the combined number of bytes ofthe data padding 202 and the data segment A 180 (i.e., the prior datasegment) is equally divisible (e.g., no remainder) by the whole wordboundary. In the illustrated embodiment, the whole word boundary may beeight bytes. In other embodiments, the whole word boundary may be anysuitable number of bytes or bits. As such, in the illustratedembodiment, if the data segment A 180 were to include 63 bytes of data,the data padding 202 would include one byte of data (e.g., to make 64combined bytes of data between the data segment A 180 and the datapadding 202, with 64 being equally divisible by eight bytes). As anotherexample, if the data segment A 180 included 60 bytes of data (e.g.,which is not equally divisible by eight), the data padding 202 wouldinclude four bytes of data. As a further example, if the data segment A180 included 64 bytes of data, the data padding 202 would include zerobytes of data, or in other words the data padding 202 would not beneeded between the data segment A 180 and the data segment F 190. Aswill be appreciated, each data padding 202, 204, 206, 208, 210, 212, and214 may operate in a similar manner.

Referring now to FIG. 13, an example of data padding inserted after datasegments of the data blocks 172, 174, 176, and 178 of FIG. 12 isillustrated. Specifically, data padding may be inserted at the end ofeach data block 172, 174, 176, and 178 as needed to make the number ofbytes in each data blocks 172, 174, 176, and 178 equal. Furthermore, thedata padding at the end of each data block 172, 174, 176, and 178 may beused so that each data block 172, 174, 176, and 178 reaches a whole wordboundary as previously described. In the illustrated embodiment, datapadding 216 is inserted after the data segment I 196, data padding 218is inserted after the data segment G 192, and data padding 220 isinserted after the data segment J 198. Accordingly, each of the datablocks 172, 174, 176, and 178 includes an equal number of bytes and eachof the data blocks 172, 174, 176, and 178 reaches a whole word boundary.

It may be difficult for FSM lattices 30 to distinguish data padding fromvalid data. Accordingly, instructions may accompany the data blocks 172,174, 176, and 178 so that data padding may be identified and disregardedby the FSM lattices 30 during analysis of the valid data. Suchinstructions may be sent to the state machine engine 14 by the processor12 via the bus interface 130 and may be received, stored, and providedby the instruction buffer 160 of the state machine engine 14. To producethe instructions, the processor 12 may logically divide the data stream170 into regions 222, 224, 226, 228, 230, 232, 234, and 236. The endboundaries of the regions 222, 224, 226, 228, 230, 232, 234, and 236 maybe formed such that each region ends when any data padding ends. Forexample, the first region 222 ends when the data padding 208 ends. Asanother example, the fifth region 230 ends when the data padding 204ends.

The instructions that accompany the data blocks 172, 174, 176, and 178may include a number of bytes for each region 222, 224, 226, 228, 230,232, 234, and 236 and a number of valid bytes (e.g., the number of bytesexcludes byte padding) for each data block 172, 174, 176, and 178 withineach region. For example, the instructions may include: a number ofbytes 238 that corresponds to the first region 222, a number of bytes240 that corresponds to the valid bytes for the first data block 172within the first region 222, a number of bytes 242 that corresponds tothe valid bytes for the second data block 174 within the first region222, a number of bytes 244 that corresponds to the valid bytes for thethird data block 176 within the first region 222, and a number of bytes246 that corresponds to the valid bytes for the fourth data block 178within the first region 222.

Likewise, the instructions may include: numbers of bytes 248, 250, 252,254, and 256 that correspond to the second region 224, numbers of bytes258, 260, 262, 264, and 266 that correspond to the third region 226,numbers of bytes 268, 270, 272, 274, and 276 that correspond to thefourth region 228, numbers of bytes 278, 280, 282, 284, and 286 thatcorrespond to the fifth region 230, numbers of bytes 288, 290, 292, 294,and 296 that correspond to the sixth region 232, numbers of bytes 298,302, 304, and 306 that correspond to the seventh region 234, and numbersof bytes 308, 312, 314, and 316 that correspond to the eighth region236. Accordingly, using the instructions, the FSM lattices 30 mayidentify the data padding inserted with the data segments. Although onespecific type of instructions has been presented herein, it should benoted that the instructions included with the group of data blocks 172,174, 176, and 178 may be any suitable group of instructions that allowthe FSM lattices 30 to distinguish valid data from data padding (i.e.,invalid data).

Referring now to FIG. 14, an example of the data blocks 172, 174, 176,and 178 of FIG. 13 organized by the processor 12 for transmission todata buffer system 159 of the state machine engines 14 is illustrated.Each of the data blocks 172, 174, 176, and 178 are arranged with rows ofdata having a number of bytes 318 equivalent to a whole word length. Inthe illustrated embodiment, the whole word length is eight bytesrepresented by a byte for each of state machine engines 14 (e.g., F0,F1, F2, F3, F4, F5, F6, and F7). The first byte from each of the datasegments begins at the right side of each data block 172, 174, 176, and178 and increase toward the left side of each data block such that thefirst byte for the data segment A 180 is in column F0 and the eighthbyte for the data segment A 180 is in column F7. As will be appreciated,the column F0 represents data that will be initially stored in the databuffers 132 of the F0 state machine engine 14, the column F1 representsdata that will be initially stored in the data buffers 132 of the F1state machine engine 14, and so forth. Furthermore, the data segmentsare placed in rows from top to bottom. As illustrated, each combinationof a data segment and data padding ends in column F7 (i.e., they eachextend for a whole word length). Furthermore, each data block 172, 174,176, and 178 is equal in size. As will be appreciated, during operationthe data blocks 172, 174, 176, and 178 may be provided from theprocessor 12 to the state machine engines 14 sequentially.

The data from the data blocks 172, 174, 176, and 178 is arranged so thatthe data intended for the logical groups 162, 164, 166, and 168 isintermingled in the data buffer system 159 such that a portion of thedata intended for each logical group 162, 164, 166, and 168 isintermingled within each state machine engine 14 (e.g., F0, F1, F2, F3,F4, F5, F6, and F7). The data may be received and stored in this mannerto enable data to be quickly provided over the bus interface 130 to thedata buffer system 159. In certain embodiments, the data buffers 132 ofthe data buffer system 159 may be configured to latch data from the businterface 130 (e.g., at predetermined intervals). In other embodiments,the data buffers 132 of the data buffer system 159 may receive a limitedportion of data based on the connection between the data buffers 132 andthe bus interface 130. As explained in detail below, the intermingleddata is sorted out when the data is provided from the data buffer system159 to the process buffers 134 via the IR bus and process bufferinterface 136.

Turning now to FIG. 15, an example of the data blocks 172, 174, 176, and178 being received by the state machine engines 14 is illustrated.Specifically, the data buffer system 159 receives the first data block172 followed by the second data block 174, the third data block 176, andthe fourth data block 178. As discussed above, each of the data blocks172, 174, 176, and 178 may be assigned by the processor 12 to beanalyzed by a particular logical group 162, 164, 166, and 168. When thedata buffer system 159 receives the data blocks 172, 174, 176, and 178,the data buffer system 159 stores data from the data blocks 172, 174,176, and 178 into buffers in a systematic manner so that data will beprovided from the data buffer system 159 to the FSM lattices 162, 164,166, and 168 correctly.

Accordingly, FIG. 16 illustrates an example of how the data blocks 172,174, 176, and 178 of FIG. 15 are stored in the data buffer system 159 ofthe state machine engine 14. In particular, data from the first datablock 172 is stored in the first row of a buffer and every fourth rowthereafter (e.g., rows 5, 9, 13, 17, etc.). Similarly, data from thesecond data block 174 is stored in the second row of the buffer andevery fourth row thereafter (e.g., rows 6, 10, 14, 18, etc.). Further,data from the third data block 176 is stored in the third row of thebuffer and every fourth row thereafter (e.g., rows 7, 11, 15, 19, etc.).In addition, data from the fourth data block 178 is stored in the fourthrow of the buffer and every fourth row thereafter (e.g., rows 8, 12, 16,20, etc.). It should be noted that some state machine engines 14 mayinclude fewer than or more than four FSM lattices 162, 164, 166, and168. Accordingly, in other embodiments, the data buffer system 159 maybe configured to store data from data blocks in another manner. Forexample, in a state machine engine 14 with eight FSM lattices, a datablock for the each FSM lattice may have data stored in one row of abuffer and every eighth row thereafter.

Referring now to FIG. 17, an example of data provided from the databuffer system 159 to multiple FSM lattices is illustrated. Specifically,data is provided out of the data buffer system 159 to the IR bus andprocess buffer interface 136 in data bursts. In one embodiment (e.g.,where the number of bytes 318 in a whole word is eight bytes), eightdata bursts are used to complete one IR bus cycle. Specifically, in afirst data burst 320, four bytes from column F0 (e.g., a byte from eachdata block 172, 174, 176, and 178) are provided to the IR bus andprocess buffer interface 136. Similarly, in a second data burst 322,four bytes from column F1 (e.g., a byte from each data block 172, 174,176, and 178) are provided to the IR bus and process buffer interface136. In a third data burst 324, four bytes from column F2 (e.g., a bytefrom each data block 172, 174, 176, and 178) are provided to the IR busand process buffer interface 136. Further, in a fourth data burst 326,four bytes from column F3 (e.g., a byte from each data block 172, 174,176, and 178) are provided to the IR bus and process buffer interface136. In a fifth data burst 328, four bytes from column F4 (e.g., a bytefrom each data block 172, 174, 176, and 178) are provided to the IR busand process buffer interface 136. Similarly, in a sixth data burst 330,four bytes from column F5 (e.g., a byte from each data block 172, 174,176, and 178) are provided to the IR bus and process buffer interface136. In a seventh data burst 332, four bytes from column F6 (e.g., abyte from each data block 172, 174, 176, and 178) are provided to the IRbus and process buffer interface 136. Further, in an eighth data burst334, four bytes from column F7 (e.g., a byte from each data block 172,174, 176, and 178) are provided to the IR bus and process bufferinterface 136. Accordingly, data is provided out of the data buffersystem 159 to the IR bus and process buffer interface 136 in asystematic matter using data bursts.

Turning to FIG. 18, an example of data providing of the data bursts 320,322, 324, 326, 328, 330, 332, and 334 into multiple logical groups 162,164, 166, and 168 is illustrated. Specifically, in the illustratedembodiment, the process buffers 134 of the logical group A 162 (e.g.,Fg, Fh) may be configured to latch the first byte of each data burst320, 322, 324, 326, 328, 330, 332, and 334 provided onto the IR bus andprocess buffer interface 136. Similarly, the process buffers 134 of thelogical group B 164 (e.g., Fe, Ff) may be configured to latch the secondbyte of each data burst 320, 322, 324, 326, 328, 330, 332, and 334provided onto the IR bus and process buffer interface 136. In addition,the process buffers 134 of the logical group C 166 (e.g., Fc, Fd) may beconfigured to latch the third byte of each data burst 320, 322, 324,326, 328, 330, 332, and 334 provided onto the IR bus and process bufferinterface 136. The process buffers 134 of the logical group D 168 (e.g.,Fa, Fb) may be configured to latch the fourth byte of each data burst320, 322, 324, 326, 328, 330, 332, and 334 provided onto the IR bus andprocess buffer interface 136.

As will be appreciated, the process buffers 134 of the logical groups162, 164, 166, and 168 may be configured to latch any byte orcombination of bytes that have been provided onto the IR bus and processbuffer interface 136. Further, the process buffer A and the processbuffer B may be configured to latch the same or different bytes. In oneembodiment, the state machine engines 14 may include fewer than orgreater than two process buffers 134. In such an embodiment, eachprocess buffer 134 may be configured to latch a specific byte that isprovided (e.g., burst) onto the IR bus and process buffer interface 136.The process buffers 134 of the logical groups 162, 164, 166, and 168 mayalso be configured to receive instructions that accompany the databursts from the data buffer system 159. By using the instructions, theprocess buffers 134 of the logical groups 162, 164, 166, and 168 maydisregard data that corresponds to a difference between a total numberof bytes in a data region and a total number of valid bytes in that dataregion.

While the invention may be susceptible to various modifications andalternative forms, specific embodiments have been shown by way ofexample in the drawings and have been described in detail herein.However, it should be understood that the invention is not intended tobe limited to the particular forms disclosed. Rather, the invention isto cover all modifications, equivalents, and alternatives falling withinthe spirit and scope of the invention as defined by the followingappended claims.

What is claimed is:
 1. A method for preparing data to be sent to a dataanalysis system, comprising: assigning data segments of a data stream toa plurality of data blocks, wherein each data segment comprises a dataset to be analyzed and each data block is configured to be provided to acorresponding state machine engine of a plurality of state machineengines; providing data padding between at least a portion of the datasegments; providing data padding at the end of the data segments of theplurality of data blocks to produce a length of each data block that isthe same; and providing the plurality of data blocks to the dataanalysis system.
 2. The method of claim 1, wherein the data paddingprovided between at least a portion of the data segments comprises atleast one byte.
 3. The method of claim 1, wherein providing data paddingbetween at least the portion of the data segments comprises providingdata padding between data segments when a number of bytes of a priordata segment is not equally divisible by a predetermined number ofbytes.
 4. The method of claim 3, wherein the predetermined number ofbytes comprises eight bytes.
 5. The method of claim 1, wherein a numberof bytes provided as data padding after a prior data segment combinedwith a number of bytes of the prior data segment results in a combinednumber of bytes equally divisible by a predetermined number of bytes. 6.The method of claim 1, wherein each data block comprises a number ofbytes equally divisible by a predetermined number of bytes.
 7. Themethod of claim 1, comprising providing a set of instructions with theplurality of data blocks, the set of instructions configured todistinguish valid data from data padding.
 8. A system, comprising: adata analysis system comprising a plurality of state machine enginesthat when in operation analyze a data stream; and a processor coupled tothe processor data analysis system to transmit the data stream to thedata analysis system, wherein the processor when in operation assignsdata segments of the data stream to a plurality of data blocks, whereineach data segment comprises a data set to be analyzed and each datablock is configured to be provided to a corresponding state machineengine of the plurality of state machine engines of the data analysisdevice, wherein the processor when in operation provides first datapadding between data segments of the data stream or provides second datapadding at the end of data segments of the data stream to produce alength of each data block that is the same, and wherein the processorwhen in operation provides the plurality of data blocks to the dataanalysis system as the data stream.
 9. The system of claim 8, whereinthe processor provides at least one byte of data not to be analyzed asthe first data padding.
 10. The system of claim 8, wherein the processorprovides the first data padding when a number of bytes of a prior datasegment is not equally divisible by a predetermined number of bytes. 11.The system of claim 10, wherein the processor provides the first datapadding when the predetermined number of bytes comprises eight bytes.12. The system of claim 8, wherein the processor provides a number ofbytes of data not to be analyzed as the second data padding based upon anumber of bytes of the prior data segment to result in a combined numberof bytes as equally divisible by a predetermined number of bytes. 13.The system of claim 8, wherein each data block comprises a number ofbytes equally divisible by a predetermined number of bytes.
 14. Thesystem of claim 8, wherein the processor provides a set of instructionswith the plurality of data blocks, the set of instructions configured todistinguish valid data from the first data padding or the second datapadding.
 15. A device, comprising: a data buffer configured to receive adata stream to be analyzed; a plurality of state machine latticescomprising a plurality of configurable elements each comprising aplurality of memory cells, wherein the plurality of configurableelements are configured to analyze at least a portion of the data streamand to output a result of the analysis; and a buffer interface coupledto the data buffer and the plurality of state machine lattices, whereinthe buffer interface is configured to receive the data stream from thedata buffer and to provide the data stream to the plurality of statemachine lattices, wherein the data stream comprises data segmentsassigned to a plurality of data blocks, wherein each data segmentcomprises a data set to be analyzed and each data block is configured tobe provided to a corresponding state machine engine of the plurality ofstate machine engines, wherein the data stream comprises first datapadding between at least a portion of the data segments or second datapadding at the end of data segment.
 16. The device of claim 15, whereinthe first data padding comprises at least one byte of data not to beanalyzed as the first data padding.
 17. The device of claim 15, whereinthe first data padding is present when a number of bytes of a prior datasegment is not equally divisible by a predetermined number of bytes. 18.The device of claim 15, wherein the processor provides a number of bytesof data not to be analyzed as the second data padding based upon anumber of bytes of the prior data segment to result in a combined numberof bytes as equally divisible by a predetermined number of bytes. 19.The device of claim 15, wherein each data block comprises a number ofbytes equally divisible by a predetermined number of bytes.
 20. Thedevice of claim 15, wherein the data buffer is configured to receive aset of instructions with the plurality of data blocks, the set ofinstructions configured to distinguish valid data from the first datapadding or the second data padding.